The role of immunomodulation in ABO-incompatible adult liver transplant recipients

2008 ◽  
Vol 23 (2) ◽  
pp. 55-62 ◽  
Author(s):  
Lucio Urbani ◽  
Alessandro Mazzoni ◽  
Irene Bianco ◽  
Tiziana Grazzini ◽  
Paolo De Simone ◽  
...  
2005 ◽  
Vol 18 (8) ◽  
pp. 960-966 ◽  
Author(s):  
Gerda Drent ◽  
Elizabeth B. Haagsma ◽  
Sabina De Geest ◽  
Aad P. van den Berg ◽  
Els M. Ten Vergert ◽  
...  

2021 ◽  
Author(s):  
Giuseppe Ancona ◽  
Laura Alagna ◽  
Andrea Lombardi ◽  
Emanuele Palomba ◽  
Valeria Castelli ◽  
...  

Liver transplantation (LT) is a life-saving strategy for patients with end-stage liver disease, hepatocellular carcinoma and acute liver failure. LT success can be hampered by several short-term and long-term complications. Among them, bacterial infections, especially due to multidrug-resistant germs, are particularly frequent with a prevalence between 19 and 33% in the first 100 days after transplantation. In the last decades, a number of studies have highlighted how gut microbiota (GM) is involved in several essential functions to ensure the intestinal homeostasis, becoming one of the most important virtual metabolic organs. GM works through different axes with other organs, and the gut-liver axis is among the most relevant and investigated ones. Any alteration or disruption of GM is defined as dysbiosis. Peculiar phenotypes of GM dysbiosis have been associated to several liver conditions and complications, such as chronic hepatitis, fatty liver disease, cirrhosis and hepatocellular carcinoma. Moreover, there is growing evidence of the crucial role of GM in shaping the immune response, both locally and systemically, against pathogens. This paves the way to the manipulation of GM as a therapeutic instrument to modulate the infectious risk and outcome. In this minireview we provide an overview of the current understanding on the interplay between gut microbiota and the immune system in liver transplant recipients and the role of the former in infections.


2019 ◽  
Vol 21 (4) ◽  
Author(s):  
Elda Righi ◽  
Alessia Carnelutti ◽  
Umberto Baccarani ◽  
Assunta Sartor ◽  
Piergiorgio Cojutti ◽  
...  

2013 ◽  
Vol 45 (8) ◽  
pp. 3057-3060 ◽  
Author(s):  
Y.-I. Choi ◽  
S. Hwang ◽  
G.-C. Park ◽  
J.-M. Namgoong ◽  
D.-H. Jung ◽  
...  

2019 ◽  
Vol 54 (7) ◽  
pp. 652-661 ◽  
Author(s):  
Jia Shao ◽  
Chenyu Wang ◽  
Peng Fu ◽  
Fan Chen ◽  
Yi Zhang ◽  
...  

Background: Tacrolimus (TAC) is widely used after liver transplantation, but the therapeutic window is narrow. Objective: The purpose was to study both donor and recipient CYP3A5*3 genotypes affecting TAC apparent clearance rate (CL/F) and investigate a TAC population pharmacokinetic (PPK) model in Chinese liver transplant recipients for potential starting-dose individualized medication. Methods: A data set of 721 TAC concentrations was obtained from 43 adult liver transplant recipients. The TAC PPK model was analyzed using nonlinear mixed-effects modeling. Potential covariates, including demographic characteristics, physiological and pathological data, concomitant medications, and CYP3A5*3 genotype, were evaluated. The final model was validated using normalized prediction distribution errors and bootstrapping. Results: A 2-compartment model with first-order absorption and elimination was used to describe TAC disposition. Population estimates of TAC, CL/F, apparent central distribution volume (V2/F), rate of absorption (Ka), and apparent peripheral distribution volume (V3/F) were 18.1 L/h (12%), 72.7 L (34%), 0.163 h−1 (17%), and 412 L (21%), respectively. The model and estimated parameters were found to be stable. Other covariates did not influence TAC CL/F. Both donor and recipient CYP3A5*1 genotypes were significantly correlated with TAC clearance, and CL/F was 1.70-fold higher in both donor and recipient CYP3A5*1 carriers than in noncarriers among Chinese liver transplant recipients. Conclusion and Relevance: A PPK model of TAC was established in Chinese adult liver transplantation recipients for starting-dose individualized medication, which can be expanded to optimize clinical efficacy and minimize toxicity with therapeutic drug monitoring.


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